🔧 Genith: Create Images and Videos with AI, Store with Pinata

🕛 Zeit seit Veröffentlichung: 94 Tage, 1 Stunden 43 Minuten
📆 Veröffentlicht am: 12.10.2024 um 16:06 Uhr
Nachrichtenbereich: 🔧 Programmierung
🔗 Quelle: dev.to

This is a submission for the The Pinata Challenge

What I Built

I built Genith, an image and video generation app that uses AI/ML technology (fal.ai) for creating content based on text prompts. For easy and secure content storage, I used Pinata, which helps manage all the generated media.

Genith enables users to create and store unique content effortlessly, all while enjoying a smooth and engaging user experience. Key features include:

• AI-Driven Generation: Users can generate stunning images and videos using advanced AI models.
• Decentralized Storage: Integrating Pinata, all generated content is securely stored on IPFS, ensuring reliable and decentralized access.
• Upvoting and Community Engagement: Users can upvote their favorite generated content, fostering a collaborative experience.
• Intuitive Interface: The app's design prioritizes user-friendly navigation, making it easily accessible.

Demo

Check out the live app here and generate awesome images for free: https://genith-ai.vercel.app

Here are some screenshots showcasing the app's features:

Image and Video Generation Interface:

Generated Content Gallery:

Upvote Feature:

My Code

The source code for Genith is available on GitHub: https://github.com/sholajegede/genith-ai

More Details

To build Genith, I needed a secure and seamless way to store and fetch every image and video generated, and that’s where Pinata came into play. Here’s the tech stack I used:

• Fal-ai: The AI/ML tech for turning text prompts into images and videos.
• Pinata: Secure and decentralized storage of all media.
• TypeScript: Type safety and improving code quality.
• Clerk: Authentication and managing user access.
• Convex.dev: Database to handle all data.
• Next.js: Fast development experience.
• Vercel: Hosting
• Tailwind CSS: Clean and modern UI design.

Team Submission: https://dev.to/sholajegede

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